Identification of Human Blood Plasma Proteins Using Spike-In Peptides in Shotgun Proteomics


  • A.T. Kopylov Institute of Biomedical Chemistry, 10 Pogodinskaya str., Moscow, 119121 Russia
  • O.V. Tikhonova Institute of Biomedical Chemistry, 10 Pogodinskaya str., Moscow, 119121 Russia
  • T.E. Farafonova Institute of Biomedical Chemistry, 10 Pogodinskaya str., Moscow, 119121 Russia
  • N.A. Petushkova Institute of Biomedical Chemistry, 10 Pogodinskaya str., Moscow, 119121 Russia
  • Yu.V. Miroshnichenko Institute of Biomedical Chemistry, 10 Pogodinskaya str., Moscow, 119121 Russia
  • V.G. Zgoda Institute of Biomedical Chemistry, 10 Pogodinskaya str., Moscow, 119121 Russia



mass spectrometry; protein identification; shotgun proteomics; spike-in peptides


LC-MS/MS allows identification of thousands of proteins in the complex proteomes. However, a significant part of a proteome remains inaccessible for identification due to the absence or poor quality of MS/MS spectra. The method described herein allows identifying the desired proteins of human blood plasma by comparing aligned chromatographic data of digested by trypsin sample and the same sample with spikedin synthetic peptides. Identification of human blood plasma proteins is archived by assigning tandem mass spectra of spiked-in peptides to the corresponding aligned chromatographic peaks of proteolytic peptides. Using the described approach we have identified 19 low abundant proteins in human blood plasma, which corresponded to 19 synthetic peptides used in the study. SRM verification of the identifications with isotopically labelled standards (SIS) confirmed the presence in the plasma of above 17 proteins.


  1. Domon, B., & Aebersold, R. (2006). Mass spectrometry and protein analysis. Science, 312(5771), 212-217. DOI
  2. James, P., Quadroni, M., Carafoli, E., & Gonnet, G. (1993). Protein identification by mass profile fingerprinting. Biochemical and biophysical research communications, 195(1), 58-64. DOI
  3. Pappin, D. J., Hojrup, P., & Bleasby, A. J. (1993). Rapid identification of proteins by peptide-mass fingerprinting. Current biology, 3(6), 327-332. DOI
  4. Henzel, W. J., Watanabe, C., & Stults, J. T. (2003). Protein identification: the origins of peptide mass fingerprinting. Journal of the American Society for Mass Spectrometry, 14(9), 931-942. DOI
  5. Camerini, S., & Mauri, P. (2015). The role of protein and peptide separation before mass spectrometry analysis in clinical proteomics. Journal of chromatography A, 1381, 1-12. DOI
  6. Miroshnichenko, Y. V., Petushkova, N. A., Teryaeva, N. B., Lisitsa, A. V., Zgoda, V. G., Belyaev, A. Y., & Potapov, A. A. (2015). Identifi cation of Central Nervous System Proteins in Human Blood Serum and Plasma. Bulletin of experimental biology and medicine, 160(1), 35-39. DOI
  7. Michalski, A., Damoc, E., Hauschild, J. P., Lange, O., Wieghaus, A., Makarov, A., ... & Horning, S. (2011). Mass spectrometry-based proteomics using Q Exactive, a high-performance benchtop quadrupole Orbitrap mass spectrometer. Molecular & Cellular Proteomics, 10(9), M111-011015. DOI
  8. Miroshnichenko, Y. V., Petushkova, N. A., Moskaleva, N. E., Teryaeva, N. B., Zgoda, V. G., Ilgisonis, E. V., & Belyaev, A. Y. (2015). The possibility of using the PlasmaDeepDive™ MRM-panel in clinical diagnostics. Biochemistry (Moscow) Supplement Series B: Biomedical Chemistry, 9(3), 283-289. DOI
  9. Michalski, A., Cox, J., & Mann, M. (2011). More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC− MS/MS. Journal of proteome research, 10(4), 1785-1793. DOI
  10. Laskay, U. A., Lobas, A. A., Srzentić, K., Gorshkov, M. V., & Tsybin, Y. O. (2013). Proteome digestion specificity analysis for rational design of extended bottom-up and middle-down proteomics experiments. Journal of proteome research, 12(12), 5558-5569. DOI
  11. Geiger, T., Cox, J., & Mann, M. (2010). Proteomics on an Orbitrap benchtop mass spectrometer using all-ion fragmentation. Molecular & Cellular Proteomics, 9(10), 2252-2261. DOI
  12. Sajic, T., Liu, Y., & Aebersold, R. (2015). Using data‐independent, high‐resolution mass spectrometry in protein biomarker research: perspectives and clinical applications. PROTEOMICS–Clinical Applications, 9(3-4), 307-321. DOI
  13. Gillet, L. C., Navarro, P., Tate, S., Röst, H., Selevsek, N., Reiter, L., ... & Aebersold, R. (2012). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Molecular & Cellular Proteomics, 11(6), O111-016717. DOI
  14. Schubert, O. T., Gillet, L. C., Collins, B. C., Navarro, P., Rosenberger, G., Wolski, W. E., ... & Aebersold, R. (2015). Building high-quality assay libraries for targeted analysis of SWATH MS data. Nature protocols, 10(3), 426. DOI
  15. Conrads, T. P., Anderson, G. A., Veenstra, T. D., Paša-Tolić, L., & Smith, R. D. (2000). Utility of accurate mass tags for proteome-wide protein identification. Analytical chemistry, 72(14), 3349-3354. DOI
  16. Palmblad, M., Ramström, M., Markides, K. E., Håkansson, P., & Bergquist, J. (2002). Prediction of chromatographic retention and protein identification in liquid chromatography/mass spectrometry. Analytical chemistry, 74(22), 5826-5830. DOI
  17. Stanley, J. R., Adkins, J. N., Slysz, G. W., Monroe, M. E., Purvine, S. O., Karpievitch, Y. V., ... & Dabney, A. R. (2011). A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics. Analytical chemistry, 83(16), 6135-6140. DOI
  18. Pridatchenko, M. L., Tarasova, I. A., Guryca, V., Kononikhin, A. S., Adams, C., Tolmachev, D. A., ... & Zubarev, R. A. (2009). Use of models of biomacromolecule separation in AMT database generation for shotgun proteomics. Biochemistry (Moscow), 74(11), 1195. DOI
  19. Bączek, T., & Kaliszan, R. (2009). Predictions of peptides' retention times in reversed‐phase liquid chromatography as a new supportive tool to improve protein identification in proteomics. Proteomics, 9(4), 835-847. DOI
  20. Kunda, P. B., Benavente, F., Catalá-Clariana, S., Giménez, E., Barbosa, J., & Sanz-Nebot, V. (2012). Identification of bioactive peptides in a functional yogurt by micro liquid chromatography time-of-flight mass spectrometry assisted by retention time prediction. Journal of Chromatography A, 1229, 121-128. DOI
  21. Moruz, L., Staes, A., Foster, J. M., Hatzou, M., Timmerman, E., Martens, L., & Käll, L. (2012). Chromatographic retention time prediction for posttranslationally modified peptides. Proteomics, 12(8), 1151-1159. DOI
  22. Lobas, A. A., Verenchikov, A. N., Goloborodko, A. A., Levitsky, L. I., & Gorshkov, M. V. (2013). Combination of Edman degradation of peptides with liquid chromatography/mass spectrometry workflow for peptide identification in bottom‐up proteomics. Rapid Communications in Mass Spectrometry, 27(3), 391-400. DOI
  23. Goloborodko, A. A., Mayerhofer, C., Zubarev, A. R., Tarasova, I. A., Gorshkov, A. V., Zubarev, R. A., & Gorshkov, M. V. (2010). Empirical approach to false discovery rate estimation in shotgun proteomics. Rapid Communications in Mass Spectrometry: An International Journal Devoted to the Rapid Dissemination of Up‐to‐the‐Minute Research in Mass Spectrometry, 24(4), 454-462. DOI
  24. Bateman, N. W., Goulding, S. P., Shulman, N. J., Gadok, A. K., Szumlinski, K. K., MacCoss, M. J., & Wu, C. C. (2014). Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA). Molecular & Cellular Proteomics, 13(1), 329-338. DOI
  25. Ting, Y. S., Egertson, J. D., Payne, S. H., Kim, S., MacLean, B., Käll, L., ... & MacCoss, M. J. (2015). Peptide-centric proteome analysis: an alternative strategy for the analysis of tandem mass spectrometry data. Molecular & Cellular Proteomics, 14(9), 2301-2307. DOI
  26. Hood, C. A., Fuentes, G., Patel, H., Page, K., Menakuru, M., & Park, J. H. (2008). Fast conventional Fmoc solid‐phase peptide synthesis with HCTU. Journal of peptide science: an official publication of the European Peptide Society, 14(1), 97-101. DOI
  27. MacLean, B., Tomazela, D. M., Shulman, N., Chambers, M., Finney, G. L., Frewen, B., ... & MacCoss, M. J. (2010). Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics, 26(7), 966-968. DOI
  28. Vizcaíno, J. A., Csordas, A., Del-Toro, N., Dianes, J. A., Griss, J., Lavidas, I., ... & Xu, Q. W. (2015). 2016 update of the PRIDE database and its related tools. Nucleic acids research, 44(D1), D447-D456. DOI
  29. Lange, V., Picotti, P., Domon, B., & Aebersold, R. (2008). Selected reaction monitoring for quantitative proteomics: a tutorial. Molecular systems biology, 4(1), 222. DOI
  30. Gianazza, E., Tremoli, E., & Banfi, C. (2014). The selected reaction monitoring/multiple reaction monitoring-based mass spectrometry approach for the accurate quantitation of proteins: clinical applications in the cardiovascular diseases. Expert review of proteomics, 11(6), 771-788. DOI
  31. Carr, S. A., Abbatiello, S. E., Ackermann, B. L., Borchers, C., Domon, B., Deutsch, E. W., ... & Liebler, D. C. (2014). Targeted peptide measurements in biology and medicine: best practices for mass spectrometry-based assay development using a fit-for-purpose approach. Molecular & Cellular Proteomics, 13(3), 907-917. DOI



How to Cite

Kopylov, A., Tikhonova, O., Farafonova, T., Petushkova, N., Miroshnichenko, Y., & Zgoda, V. (2019). Identification of Human Blood Plasma Proteins Using Spike-In Peptides in Shotgun Proteomics. Biomedical Chemistry: Research and Methods, 2(2), e00093.